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Information technology acceptance models provide a means to understand which aspects of e-health are valued by patients and how this may affect future use. In addition, antecedents to the models can be used to predict e-health acceptance in advance of system development.

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Research ArticleExpectation disconfirmation theory (EDT) posits that expectations, disconfirmation, and performance influence customer satisfaction. While information systems researchers have adopted EDT to explain user information technology (IT) satisfaction, they often use various EDT model subsets. Leaving out one or more key variables, or key relationships among the variables, can reduce EDT's explanatory potential. It can also suggest an intervention for practice that is very different from (and inferior to) the intervention suggested by a more complete model. Performance is an especially beneficial but largely neglected EDT construct in IT research. Using EDT theory from the marketing literature, this paper explains and demonstrates the incremental value of using the complete IT EDT model with performance versus the simplified model without it. Studying software users, we find that the complete model with performance both reveals assimilation effects for less experienced users and uncovers asymmetric effects not found in the simplified model. We also find that usefulness performance more strongly influences usage continuance intention than does any other EDT variable. We explain how researchers and practitioners can take full advantage of the predictive and explanatory power of the complete IT EDT model.We understand that researchers justifiably favor the more parsimonious of two models. For example, the technology acceptance model (TAM) is often favored over other models (e.g., the theory of reasoned action or the theory of planned behavior) for studying IT acceptance because it predicts well with fewer variables. While parsimony is important, an overly parsimonious model may not explain a phenomenon as well as a rival model. We will argue that the simplified EDT model often does not explain as well as the complete EDT model. In the process, we use arguments from the marketing EDT literature, based on such foundations as social judgment theory and prospect theory.Assessing the use of these models, we find that despite the growing number of IT EDT studies, little IT research to date examines the simplified model, and no IT EDT research to date examines the Lankton & McKnight / Examining Two EDT Models 90 Note: The shaded (black) boxes represent the relationships tested in each study. *These studies also examine the satisfaction to continuance intention relationship. E = Expectations, D = Disconfirmation, P = Performance, S = Satisfaction.